Host Institution (HI)THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN

Call DetailsConsolidator Grant (CoG), PE8, ERC-2015-CoG

SummaryMy vision is to establish, within the framework of an ERC CoG, a multidisciplinary group which will work in concert towards pioneering the integration of novel 2-Dimensional nanomaterials with novel additive fabrication techniques to develop a unique class of energy storage devices.
Batteries and supercapacitors are two very complementary types of energy storage devices. Batteries store much higher energy densities; supercapacitors, on the other hand, hold one tenth of the electricity per unit of volume or weight as compared to batteries but can achieve much higher power densities. Technology is currently striving to improve the power density of batteries and the energy density of supercapacitors. To do so it is imperative to develop new materials, chemistries and manufacturing strategies.
3D2DPrint aims to develop micro-energy devices (both supercapacitors and batteries), technologies particularly relevant in the context of the emergent industry of micro-electro-mechanical systems and constantly downsized electronics. We plan to use novel two-dimensional (2D) nanomaterials obtained by liquid-phase exfoliation. This method offers a new, economic and easy way to prepare ink of a variety of 2D systems, allowing to produce wide device performance window through elegant and simple constituent control at the point of fabrication. 3D2DPrint will use our expertise and know-how to allow development of advanced AM methods to integrate dissimilar nanomaterial blends and/or “hybrids” into fully embedded 3D printed energy storage devices, with the ultimate objective to realise a range of products that contain the above described nanomaterials subcomponent devices, electrical connections and traditional micro-fabricated subcomponents (if needed) ideally using a single tool.

My vision is to establish, within the framework of an ERC CoG, a multidisciplinary group which will work in concert towards pioneering the integration of novel 2-Dimensional nanomaterials with novel additive fabrication techniques to develop a unique class of energy storage devices.
Batteries and supercapacitors are two very complementary types of energy storage devices. Batteries store much higher energy densities; supercapacitors, on the other hand, hold one tenth of the electricity per unit of volume or weight as compared to batteries but can achieve much higher power densities. Technology is currently striving to improve the power density of batteries and the energy density of supercapacitors. To do so it is imperative to develop new materials, chemistries and manufacturing strategies.
3D2DPrint aims to develop micro-energy devices (both supercapacitors and batteries), technologies particularly relevant in the context of the emergent industry of micro-electro-mechanical systems and constantly downsized electronics. We plan to use novel two-dimensional (2D) nanomaterials obtained by liquid-phase exfoliation. This method offers a new, economic and easy way to prepare ink of a variety of 2D systems, allowing to produce wide device performance window through elegant and simple constituent control at the point of fabrication. 3D2DPrint will use our expertise and know-how to allow development of advanced AM methods to integrate dissimilar nanomaterial blends and/or “hybrids” into fully embedded 3D printed energy storage devices, with the ultimate objective to realise a range of products that contain the above described nanomaterials subcomponent devices, electrical connections and traditional micro-fabricated subcomponents (if needed) ideally using a single tool.

Max ERC Funding

2 499 942 €

Duration

Start date: 2016-10-01, End date: 2021-09-30

Project acronymACAP

ProjectAsset Centric Adaptive Protection

Researcher (PI)Bashar NUSEIBEH

Host Institution (HI)UNIVERSITY OF LIMERICK

Call DetailsProof of Concept (PoC), PC1, ERC-2015-PoC

SummaryThe proliferation of mobile and ubiquitous computing technology is radically changing the ways in which we live our lives: from interacting with friends & family, to how we produce & consume services and engage in business. However, this pervasiveness of technologies, and their increasingly seamless integration and inter-operation, are blurring the boundaries between systems. This poses significant challenges for security engineers who aim to design systems that monitor and control the movement of digital or physical assets across those boundaries.
My ERC Advanced Grant on Adaptive Security and Privacy (ASAP) is investigating ways in which security controls can change in response to changes in the context of operation of systems. However, since the monitoring of such elusive and changing boundaries is difficult, we have developed an adaptive security approach that monitors valuable assets that are managed by a system, and changes the means and extent by which those assets are protected in response to changes in assets and their values. This could radically change the way security is designed and implemented in a range of applications because it allows for a choice of appropriate protection, depending on particular requirements.
In ASAP, we developed the modelling and computational capabilities of our approach, including some prototype tool fragments that demonstrate the approach in our lab. However, interest from our industrial collaborators, evidenced by direct funding of follow-on research, and the demonstration of our prototypes to senior management and potential customers, has motivated us to pursue a proof of concept (PoC) assessment of our work in a more systematic and targeted way. To this end, this ERC PoC will:
1) Develop a robust prototype demonstrator, instantiated in two application areas (access control & cloud computing);
2) Conduct a market analysis, aided by the demonstrator;
3) Subject to (2), develop a commercialisation strategy and plan

The proliferation of mobile and ubiquitous computing technology is radically changing the ways in which we live our lives: from interacting with friends & family, to how we produce & consume services and engage in business. However, this pervasiveness of technologies, and their increasingly seamless integration and inter-operation, are blurring the boundaries between systems. This poses significant challenges for security engineers who aim to design systems that monitor and control the movement of digital or physical assets across those boundaries.
My ERC Advanced Grant on Adaptive Security and Privacy (ASAP) is investigating ways in which security controls can change in response to changes in the context of operation of systems. However, since the monitoring of such elusive and changing boundaries is difficult, we have developed an adaptive security approach that monitors valuable assets that are managed by a system, and changes the means and extent by which those assets are protected in response to changes in assets and their values. This could radically change the way security is designed and implemented in a range of applications because it allows for a choice of appropriate protection, depending on particular requirements.
In ASAP, we developed the modelling and computational capabilities of our approach, including some prototype tool fragments that demonstrate the approach in our lab. However, interest from our industrial collaborators, evidenced by direct funding of follow-on research, and the demonstration of our prototypes to senior management and potential customers, has motivated us to pursue a proof of concept (PoC) assessment of our work in a more systematic and targeted way. To this end, this ERC PoC will:
1) Develop a robust prototype demonstrator, instantiated in two application areas (access control & cloud computing);
2) Conduct a market analysis, aided by the demonstrator;
3) Subject to (2), develop a commercialisation strategy and plan

SummaryTumor Necrosis Factor (TNF) is a homotrimeric pro-inflammatory cytokine that was originally discovered based on its extraordinary antitumor activity. However, its shock-inducing properties, causing hypotension, leukopenia and multiple organ failure, prevented its systemic use in cancer treatment. With this proof-of-concept study we want to evaluate a novel class of cell-targeted TNFs with strongly reduced systemic toxicities (AcTafactors). In these engineered immuno-cytokines, single-chain TNFs that harbor mutations to reduce the affinity for its receptor(s) are fused to a cell- specific targeting domain. Whilst almost no biological activity is observed on non-targeted cells, thus preventing systemic toxicity, avidity effects at the targeted cell membrane lead to recovery of over 90% of the TNF signaling activity. In this project we propose a lead optimization program to further improve the lead AcTafactors identified in the context of the ERC Advanced Grant project and to evaluate the resulting molecules for their ability to target the tumor (neo)vasculature in clinically relevant murine tumor models. The pre-clinical proof-of-concept we aim for represents a first step towards clinical development and ultimately potential market approval of an effective AcTafactor anti-cancer therapy.

Tumor Necrosis Factor (TNF) is a homotrimeric pro-inflammatory cytokine that was originally discovered based on its extraordinary antitumor activity. However, its shock-inducing properties, causing hypotension, leukopenia and multiple organ failure, prevented its systemic use in cancer treatment. With this proof-of-concept study we want to evaluate a novel class of cell-targeted TNFs with strongly reduced systemic toxicities (AcTafactors). In these engineered immuno-cytokines, single-chain TNFs that harbor mutations to reduce the affinity for its receptor(s) are fused to a cell- specific targeting domain. Whilst almost no biological activity is observed on non-targeted cells, thus preventing systemic toxicity, avidity effects at the targeted cell membrane lead to recovery of over 90% of the TNF signaling activity. In this project we propose a lead optimization program to further improve the lead AcTafactors identified in the context of the ERC Advanced Grant project and to evaluate the resulting molecules for their ability to target the tumor (neo)vasculature in clinically relevant murine tumor models. The pre-clinical proof-of-concept we aim for represents a first step towards clinical development and ultimately potential market approval of an effective AcTafactor anti-cancer therapy.

Max ERC Funding

149 320 €

Duration

Start date: 2015-11-01, End date: 2017-04-30

Project acronymAD-VIP

ProjectAlzheimer’s disease and AAV9: Use of a virus-based delivery system for vectored immunoprophylaxis in dementia.

Researcher (PI)MATTHEW GUY HOLT

Host Institution (HI)VIB

Call DetailsProof of Concept (PoC), PC1, ERC-2015-PoC

SummaryAlzheimer’s disease (AD) is the most common form of dementia in the Western World, representing an economic and social cost of billions of euros a year. Given the changing demographics of society, these costs will only increase over the coming decades.
Amyloid plaques, composed of amyloid beta peptide (Abeta), are a defining characteristic of AD. Evidence now suggests that Abeta is central to disease pathogenesis due to its toxicity, which leads to cell loss and eventual cognitive decline. Abeta is generated by proteolytic cleavage of amyloid precursor protein, a process that involves the protein BACE1.
Knock-down of BACE1 is sufficient to prevent amyloid pathology and cognitive deficits in transgenic mouse models of AD, so BACE1 is an attractive target for therapeutic intervention. Although many small molecule inhibitors of BACE1 have been developed, many have problems with imperfect selectivity, posing a substantial risk for off-target toxicity in vivo. In contrast, antibody-based therapeutics provide an attractive alternative given their excellent molecular selectivity. However, the success of antibody therapies in AD is limited by the blood brain barrier, which limits antibody entry into the brain from the systemic circulation.
Recent studies have shown that adeno-associated virus serotype 9 (AAV9) effectively crosses the blood brain barrier. Here, we propose evaluating the use of AAV9 as a delivery system for a highly specific and potent inhibitory nanobody targeted against BACE1 as a treatment for AD.

Alzheimer’s disease (AD) is the most common form of dementia in the Western World, representing an economic and social cost of billions of euros a year. Given the changing demographics of society, these costs will only increase over the coming decades.
Amyloid plaques, composed of amyloid beta peptide (Abeta), are a defining characteristic of AD. Evidence now suggests that Abeta is central to disease pathogenesis due to its toxicity, which leads to cell loss and eventual cognitive decline. Abeta is generated by proteolytic cleavage of amyloid precursor protein, a process that involves the protein BACE1.
Knock-down of BACE1 is sufficient to prevent amyloid pathology and cognitive deficits in transgenic mouse models of AD, so BACE1 is an attractive target for therapeutic intervention. Although many small molecule inhibitors of BACE1 have been developed, many have problems with imperfect selectivity, posing a substantial risk for off-target toxicity in vivo. In contrast, antibody-based therapeutics provide an attractive alternative given their excellent molecular selectivity. However, the success of antibody therapies in AD is limited by the blood brain barrier, which limits antibody entry into the brain from the systemic circulation.
Recent studies have shown that adeno-associated virus serotype 9 (AAV9) effectively crosses the blood brain barrier. Here, we propose evaluating the use of AAV9 as a delivery system for a highly specific and potent inhibitory nanobody targeted against BACE1 as a treatment for AD.

Max ERC Funding

150 000 €

Duration

Start date: 2016-12-01, End date: 2018-05-31

Project acronymATTO

ProjectA new concept for ultra-high capacity wireless networks

Researcher (PI)Piet DEMEESTER

Host Institution (HI)UNIVERSITEIT GENT

Call DetailsAdvanced Grant (AdG), PE7, ERC-2015-AdG

SummaryThe project will address the following key question:
How can we provide fibre-like connectivity to moving objects (robots, humans) with the following characteristics: very high dedicated bitrate of 100 Gb/s per object, very low latency of <10 μs, very high reliability of 99.999%, very high density of more than one object per m2 and this at low power consumption?
Achieving this would be groundbreaking and it requires a completely new and high-risk approach: applying close proximity wireless communications using low interference ultra-small cells (called “ATTO-cells”) integrated in floors and connected to antennas on the (parallel) floor-facing surface of ground moving objects. This makes it possible to obtain very high densities with very good channel conditions. The technological challenges involved are groundbreaking in mobile networking (overall architecture, handover with extremely low latencies), wireless subsystems (60 GHz substrate integrated waveguide-based distributed antenna systems connected to RF transceivers integrated in floors, low crosstalk between ATTO-cells) and optical interconnect subsystems (simple non-blocking optical coherent remote selection of ATTO-cells, transparent low power 100 Gb/s coherent optical / RF transceiver interconnection using analogue equalization and symbol interleaving to support 4x4 MIMO). By providing this unique communication infrastructure in high density settings, the ATTO concept will not only support the highly demanding future 5G services (UHD streaming, cloud computing and storage, augmented and virtual reality, a range of IoT services, etc.), but also even more demanding services, that are challenging our imagination such as mobile robot swarms or brain computer interfaces with PFlops computing capabilities.
This new concept for ultra-high capacity wireless networks will open up many more opportunities in reconfigurable robot factories, intelligent hospitals, flexible offices, dense public spaces, etc.

The project will address the following key question:
How can we provide fibre-like connectivity to moving objects (robots, humans) with the following characteristics: very high dedicated bitrate of 100 Gb/s per object, very low latency of <10 μs, very high reliability of 99.999%, very high density of more than one object per m2 and this at low power consumption?
Achieving this would be groundbreaking and it requires a completely new and high-risk approach: applying close proximity wireless communications using low interference ultra-small cells (called “ATTO-cells”) integrated in floors and connected to antennas on the (parallel) floor-facing surface of ground moving objects. This makes it possible to obtain very high densities with very good channel conditions. The technological challenges involved are groundbreaking in mobile networking (overall architecture, handover with extremely low latencies), wireless subsystems (60 GHz substrate integrated waveguide-based distributed antenna systems connected to RF transceivers integrated in floors, low crosstalk between ATTO-cells) and optical interconnect subsystems (simple non-blocking optical coherent remote selection of ATTO-cells, transparent low power 100 Gb/s coherent optical / RF transceiver interconnection using analogue equalization and symbol interleaving to support 4x4 MIMO). By providing this unique communication infrastructure in high density settings, the ATTO concept will not only support the highly demanding future 5G services (UHD streaming, cloud computing and storage, augmented and virtual reality, a range of IoT services, etc.), but also even more demanding services, that are challenging our imagination such as mobile robot swarms or brain computer interfaces with PFlops computing capabilities.
This new concept for ultra-high capacity wireless networks will open up many more opportunities in reconfigurable robot factories, intelligent hospitals, flexible offices, dense public spaces, etc.

Max ERC Funding

2 496 250 €

Duration

Start date: 2017-01-01, End date: 2021-12-31

Project acronymBEAL

ProjectBioenergetics in microalgae : regulation modes of mitochondrial respiration, photosynthesis, and fermentative pathways, and their interactions in secondary algae

Researcher (PI)Pierre Antoine Georges Cardol

Host Institution (HI)UNIVERSITE DE LIEGE

Call DetailsConsolidator Grant (CoG), LS8, ERC-2015-CoG

SummaryDuring the course of eukaryote evolution, photosynthesis was propagated from primary eukaryotic algae to non-photosynthetic organisms through multiple secondary endosymbiotic events. Collectively referred to as “secondary algae”, these photosynthetic organisms account for only 1-2% of the total global biomass, but produce a far larger part of the global annual fixation of carbon on Earth.
ATP is the universal chemical energy carrier in living cells. In photosynthetic eukaryotes, it is produced by two major cellular processes: photosynthesis and respiration taking place in chloroplasts and mitochondria, respectively. Both processes support the production of biomass and govern gas (O2 and CO2) exchanges. On the other hand, anaerobic fermentative enzymes have also been identified in several primary and secondary algae. The regulation modes and interactions of respiration, photosynthesis and fermentation are fairly well understood in primary green algae. Conversely, the complex evolutionary history of secondary algae implies a great variety of original regulatory mechanisms that have been barely investigated to date.
Over the last years my laboratory has developed and optimized a range of multidisciplinary approaches that now allow us, within the frame of the BEAL (BioEnergetics in microALgae) project, to (i) characterize and compare the photosynthetic regulation modes by biophysical approaches, (ii) use genetic and biochemical approaches to gain fundamental knowledge on aerobic respiration and anaerobic fermentative pathways, and (iii) investigate and compare interconnections between respiration, photosynthesis, and fermentation in organisms resulting from distinct evolutionary scenarios. On a long term, these developments will be instrumental to unravel bioenergetics constraints on growth in microalgae, a required knowledge to exploit the microalgal diversity in a biotechnological perspective, and to understand the complexity of the marine phytoplankton.

During the course of eukaryote evolution, photosynthesis was propagated from primary eukaryotic algae to non-photosynthetic organisms through multiple secondary endosymbiotic events. Collectively referred to as “secondary algae”, these photosynthetic organisms account for only 1-2% of the total global biomass, but produce a far larger part of the global annual fixation of carbon on Earth.
ATP is the universal chemical energy carrier in living cells. In photosynthetic eukaryotes, it is produced by two major cellular processes: photosynthesis and respiration taking place in chloroplasts and mitochondria, respectively. Both processes support the production of biomass and govern gas (O2 and CO2) exchanges. On the other hand, anaerobic fermentative enzymes have also been identified in several primary and secondary algae. The regulation modes and interactions of respiration, photosynthesis and fermentation are fairly well understood in primary green algae. Conversely, the complex evolutionary history of secondary algae implies a great variety of original regulatory mechanisms that have been barely investigated to date.
Over the last years my laboratory has developed and optimized a range of multidisciplinary approaches that now allow us, within the frame of the BEAL (BioEnergetics in microALgae) project, to (i) characterize and compare the photosynthetic regulation modes by biophysical approaches, (ii) use genetic and biochemical approaches to gain fundamental knowledge on aerobic respiration and anaerobic fermentative pathways, and (iii) investigate and compare interconnections between respiration, photosynthesis, and fermentation in organisms resulting from distinct evolutionary scenarios. On a long term, these developments will be instrumental to unravel bioenergetics constraints on growth in microalgae, a required knowledge to exploit the microalgal diversity in a biotechnological perspective, and to understand the complexity of the marine phytoplankton.

Max ERC Funding

1 837 625 €

Duration

Start date: 2016-06-01, End date: 2021-05-31

Project acronymCathedral

ProjectPost-Snowden Circuits and Design Methods for Security

Researcher (PI)Ingrid VERBAUWHEDE

Host Institution (HI)KATHOLIEKE UNIVERSITEIT LEUVEN

Call DetailsAdvanced Grant (AdG), PE7, ERC-2015-AdG

SummarySummary: Comprehensive set of circuits and design methods to create next generation electronic circuits with strong built-in trust and security.
Electronics are integrating/invading into the human environment at an amazing speed, called the Internet-of-Things and next the Internet-of-Everything. This creates huge security problems. Distributed (e.g. body) sensors, pick up often very private data, which is sent digitally into the cloud, over wireless and wired links. Protection of this data relies on high-quality cryptographic algorithms and protocols. The nodes need to be cheap and lightweight, making them very vulnerable to eavesdropping and abuse. Moreover, post-Snowden, society realizes that the attack capabilities of intelligence agencies, and probably following soon of organized crime and other hackers, are orders of magnitude stronger than imagined. Thus there is a strong demand to re-establish trust in ICT systems.
In this proposal we focus on the root of trust: the digital hardware. The overall objective is to provide fundamental enabling technologies for secure trustworthy digital circuits which can be applied in a wide range of applications. To master complexity, digital hardware design is traditionally split into different abstraction layers. We revisit these abstraction layers from a security viewpoint: we look at process variations to the benefit of security, standard cell compatible digital design flow with security as design objective, hardware IP blocks for next generation cryptographic algorithms and protocols (e.g. authenticated encryption schemes, post-quantum public key schemes), integration into embedded HW/SW platforms, and methods to provide trust evidence to higher levels of abstraction. To strengthen the security we investigate the links between the layers. Finally an embedded application is selected as design driver, the security evaluation of which will be fed back to the individual layers.

Summary: Comprehensive set of circuits and design methods to create next generation electronic circuits with strong built-in trust and security.
Electronics are integrating/invading into the human environment at an amazing speed, called the Internet-of-Things and next the Internet-of-Everything. This creates huge security problems. Distributed (e.g. body) sensors, pick up often very private data, which is sent digitally into the cloud, over wireless and wired links. Protection of this data relies on high-quality cryptographic algorithms and protocols. The nodes need to be cheap and lightweight, making them very vulnerable to eavesdropping and abuse. Moreover, post-Snowden, society realizes that the attack capabilities of intelligence agencies, and probably following soon of organized crime and other hackers, are orders of magnitude stronger than imagined. Thus there is a strong demand to re-establish trust in ICT systems.
In this proposal we focus on the root of trust: the digital hardware. The overall objective is to provide fundamental enabling technologies for secure trustworthy digital circuits which can be applied in a wide range of applications. To master complexity, digital hardware design is traditionally split into different abstraction layers. We revisit these abstraction layers from a security viewpoint: we look at process variations to the benefit of security, standard cell compatible digital design flow with security as design objective, hardware IP blocks for next generation cryptographic algorithms and protocols (e.g. authenticated encryption schemes, post-quantum public key schemes), integration into embedded HW/SW platforms, and methods to provide trust evidence to higher levels of abstraction. To strengthen the security we investigate the links between the layers. Finally an embedded application is selected as design driver, the security evaluation of which will be fed back to the individual layers.

SummaryLow-rank matrix approximation (LRA) techniques such as principal component analysis (PCA) are powerful tools for the representation and analysis of high dimensional data, and are used in a wide variety of areas such as machine learning, signal and image processing, data mining, and optimization. Without any constraints and using the least squares error, LRA can be solved via the singular value decomposition. However, in practice, this model is often not suitable mainly because (i) the data might be contaminated with outliers, missing data and non-Gaussian noise, and (ii) the low-rank factors of the decomposition might have to satisfy some specific constraints. Hence, in recent years, many variants of LRA have been introduced, using different constraints on the factors and using different objective functions to assess the quality of the approximation; e.g., sparse PCA, PCA with missing data, independent component analysis and nonnegative matrix factorization. Although these new constrained LRA models have become very popular and standard in some fields, there is still a significant gap between theory and practice. In this project, our goal is to reduce this gap by attacking the problem in an integrated way making connections between LRA variants, and by using four very different but complementary perspectives: (1) computational complexity issues, (2) provably correct algorithms, (3) heuristics for difficult instances, and (4) application-oriented aspects. This unified and multi-disciplinary approach will enable us to understand these problems better, to develop and analyze new and existing algorithms and to then use them for applications. Our ultimate goal is to provide practitioners with new tools and to allow them to decide which method to use in which situation and to know what to expect from it.

Low-rank matrix approximation (LRA) techniques such as principal component analysis (PCA) are powerful tools for the representation and analysis of high dimensional data, and are used in a wide variety of areas such as machine learning, signal and image processing, data mining, and optimization. Without any constraints and using the least squares error, LRA can be solved via the singular value decomposition. However, in practice, this model is often not suitable mainly because (i) the data might be contaminated with outliers, missing data and non-Gaussian noise, and (ii) the low-rank factors of the decomposition might have to satisfy some specific constraints. Hence, in recent years, many variants of LRA have been introduced, using different constraints on the factors and using different objective functions to assess the quality of the approximation; e.g., sparse PCA, PCA with missing data, independent component analysis and nonnegative matrix factorization. Although these new constrained LRA models have become very popular and standard in some fields, there is still a significant gap between theory and practice. In this project, our goal is to reduce this gap by attacking the problem in an integrated way making connections between LRA variants, and by using four very different but complementary perspectives: (1) computational complexity issues, (2) provably correct algorithms, (3) heuristics for difficult instances, and (4) application-oriented aspects. This unified and multi-disciplinary approach will enable us to understand these problems better, to develop and analyze new and existing algorithms and to then use them for applications. Our ultimate goal is to provide practitioners with new tools and to allow them to decide which method to use in which situation and to know what to expect from it.

Max ERC Funding

1 291 750 €

Duration

Start date: 2016-09-01, End date: 2021-08-31

Project acronymCOSMOS

ProjectSemiparametric Inference for Complex and Structural Models in Survival Analysis

Researcher (PI)Ingrid VAN KEILEGOM

Host Institution (HI)KATHOLIEKE UNIVERSITEIT LEUVEN

Call DetailsAdvanced Grant (AdG), PE1, ERC-2015-AdG

SummaryIn survival analysis investigators are interested in modeling and analysing the time until an event happens. It often happens that the available data are right censored, which means that only a lower bound of the time of interest is observed. This feature complicates substantially the statistical analysis of this kind of data. The aim of this project is to solve a number of open problems related to time-to-event data, that would represent a major step forward in the area of survival analysis.
The project has three objectives:
[1] Cure models take into account that a certain fraction of the subjects under study will never experience the event of interest. Because of the complex nature of these models, many problems are still open and rigorous theory is rather scarce in this area. Our goal is to fill this gap, which will be a challenging but important task.
[2] Copulas are nowadays widespread in many areas in statistics. However, they can contribute more substantially to resolving a number of the outstanding issues in survival analysis, such as in quantile regression and dependent censoring. Finding answers to these open questions, would open up new horizons for a wide variety of problems.
[3] We wish to develop new methods for doing correct inference in some of the common models in survival analysis in the presence of endogeneity or measurement errors. The present methodology has serious shortcomings, and we would like to propose, develop and validate new methods, that would be a major breakthrough if successful.
The above objectives will be achieved by using mostly semiparametric models. The development of mathematical properties under these models is often a challenging task, as complex tools from the theory on empirical processes and semiparametric efficiency are required. The project will therefore require an innovative combination of highly complex mathematical skills and cutting edge results from modern theory for semiparametric models.

In survival analysis investigators are interested in modeling and analysing the time until an event happens. It often happens that the available data are right censored, which means that only a lower bound of the time of interest is observed. This feature complicates substantially the statistical analysis of this kind of data. The aim of this project is to solve a number of open problems related to time-to-event data, that would represent a major step forward in the area of survival analysis.
The project has three objectives:
[1] Cure models take into account that a certain fraction of the subjects under study will never experience the event of interest. Because of the complex nature of these models, many problems are still open and rigorous theory is rather scarce in this area. Our goal is to fill this gap, which will be a challenging but important task.
[2] Copulas are nowadays widespread in many areas in statistics. However, they can contribute more substantially to resolving a number of the outstanding issues in survival analysis, such as in quantile regression and dependent censoring. Finding answers to these open questions, would open up new horizons for a wide variety of problems.
[3] We wish to develop new methods for doing correct inference in some of the common models in survival analysis in the presence of endogeneity or measurement errors. The present methodology has serious shortcomings, and we would like to propose, develop and validate new methods, that would be a major breakthrough if successful.
The above objectives will be achieved by using mostly semiparametric models. The development of mathematical properties under these models is often a challenging task, as complex tools from the theory on empirical processes and semiparametric efficiency are required. The project will therefore require an innovative combination of highly complex mathematical skills and cutting edge results from modern theory for semiparametric models.

Max ERC Funding

2 318 750 €

Duration

Start date: 2016-09-01, End date: 2021-08-31

Project acronymCrUCCial

ProjectNovel diagnostic and therapeutic approach to inflammatory bowel disease based on functional characterization of patients: the CrUCCial index

Researcher (PI)Severine VERMEIRE

Host Institution (HI)KATHOLIEKE UNIVERSITEIT LEUVEN

Call DetailsAdvanced Grant (AdG), LS7, ERC-2015-AdG

SummaryThe clinical phenotype and the outcome of Crohn's disease (CD) and ulcerative colitis (UC), the opposite ends of chronic inflammatory bowel diseases (IBD), are heterogeneous and represent the result of a complex interplay of the gut microbiome with the immune system in genetically predisposed individuals. Disease management is much less heterogeneous as all patients are treated using non-specific anti-inflammatory agents, and only 30-50% achieve clinical and mucosal remission -the goal of therapy nowadays- therefore leaving large margins for improvement. The advances in knowledge about the factors triggering disease onset should be translated to approach the disease from a molecular angle. Key cellular pathways have emerged including bacterial recognition, autophagy, endoplasmic reticulum stress and intestinal barrier function. Functional/molecular characterization of these pathways in a given patient, correlation with meaningful clinical outcomes, and tailoring an individual therapeutic approach has never been attempted and will represent a breakthrough in the current paradigm of treating multifactorial inflammatory conditions. This project aims to functionally characterize patients with CD/UC for the major pathways by using integrated (epi)genetic, transcriptomic, immunologic, barrier integrity and metagenomic studies. From these readouts we will construct an index [the Crohn’s and Ulcerative Colitis Characterization and Intervention trial (CrUCCial) index], reflecting the proportional contribution of each of the pathogenic mechanisms in a given patient. We will next study the correlation of this index and its components to meaningful clinical outcomes and finally, the index will be tested in a pilot study of newly diagnosed patients in whom the disease will be targeted individually based on the components of the CrUCCial index. Our approach, from diagnosis over prognosis to therapy, will revolutionize the paradigm of disease management.

The clinical phenotype and the outcome of Crohn's disease (CD) and ulcerative colitis (UC), the opposite ends of chronic inflammatory bowel diseases (IBD), are heterogeneous and represent the result of a complex interplay of the gut microbiome with the immune system in genetically predisposed individuals. Disease management is much less heterogeneous as all patients are treated using non-specific anti-inflammatory agents, and only 30-50% achieve clinical and mucosal remission -the goal of therapy nowadays- therefore leaving large margins for improvement. The advances in knowledge about the factors triggering disease onset should be translated to approach the disease from a molecular angle. Key cellular pathways have emerged including bacterial recognition, autophagy, endoplasmic reticulum stress and intestinal barrier function. Functional/molecular characterization of these pathways in a given patient, correlation with meaningful clinical outcomes, and tailoring an individual therapeutic approach has never been attempted and will represent a breakthrough in the current paradigm of treating multifactorial inflammatory conditions. This project aims to functionally characterize patients with CD/UC for the major pathways by using integrated (epi)genetic, transcriptomic, immunologic, barrier integrity and metagenomic studies. From these readouts we will construct an index [the Crohn’s and Ulcerative Colitis Characterization and Intervention trial (CrUCCial) index], reflecting the proportional contribution of each of the pathogenic mechanisms in a given patient. We will next study the correlation of this index and its components to meaningful clinical outcomes and finally, the index will be tested in a pilot study of newly diagnosed patients in whom the disease will be targeted individually based on the components of the CrUCCial index. Our approach, from diagnosis over prognosis to therapy, will revolutionize the paradigm of disease management.